class_docstr: Apply Gaussian Blur to the PIL image. Take the radius and probability of
  application as the parameter.
  
  This transform was used in SimCLR - https://arxiv.org/abs/2002.05709
code: def __call__(self, img):
      should_blur = np.random.rand() <= self.prob
      if not should_blur:
          return img
  
      return img.filter(
          ImageFilter.GaussianBlur(
              radius=random.uniform(self.radius_min, self.radius_max)
          )
      )
  
file_path: vissl/vissl/data/ssl_transforms/img_pil_gaussian_blur.py
imports: import random
  from typing import Any, Dict
  import numpy
  from classy_vision.dataset.transforms import register_transform
  from classy_vision.dataset.transforms.classy_transform import ClassyTransform
  from PIL import ImageFilter
label_desc: Use image node_id 2 for calling the ImgPilGaussianBlur obj's underlying member method code with example usage: obj.__call__(img) and returns: img, img